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F# is a functional programming language that can now be used across platforms like Mac and Linux through the MonoDevelop IDE and F# add-in. This provides IntelliSense and an interactive environment for F#. The presentation demonstrated how F# can be used in academia for teaching functional programming, processing scientific data, and programming language research. Universities are encouraged to use F# for classes on programming concepts and data analysis or statistics work.
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Doing data science with F# (BuildStuff)
The ability to take data, understand it, visualize it and extract useful information from it is becoming a hugely important skill. How can you turn all those logs, histories of purchases and trades or open government data, into useful information that help your business make money?
In this talk, we’ll look at doing data science using F#. The F# language is perfectly suited for this task – type providers integrate external data directly into the language – your language suddenly _understands_ CSV, XML, JSON, REST services and other sources. The interactive development style makes it easy to explore data and test your algorithms as you’re writing them. Rich set of libraries for working with data frames, time series and for visualization gives you all the tools you need. And finally – F# easily integrates with statistical environments like R and Matlab, giving you access to the industry standard libraries.
Doing data science with F#
The ability to take data, understand it, visualize it and extract useful information from it is becoming a hugely important skill. How can you turn all those logs, histories of purchases and trades or open government data, into useful information that help your business make money?
In this talk, we’ll look at doing data science using F#. The F# language is perfectly suited for this task – type providers integrate external data directly into the language – your language suddenly _understands_ CSV, XML, JSON, REST services and other sources. The interactive development style makes it easy to explore data and test your algorithms as you’re writing them. Rich set of libraries for working with data frames, time series and for visualization gives you all the tools you need. And finally – F# easily integrates with statistical environments like R and Matlab, giving you access to the industry standard libraries.
F# and Financial Data Making Data Analysis Simple
This document discusses F# and its use for financial data analysis. It introduces Tomas Petricek and his work contributing to F# and authoring books on functional programming. It also discusses BlueMountain Capital, where Tomas worked briefly and where F# is used for trading strategies. The document then describes the F# Data Science Working Group and its libraries for data acquisition, cleaning, transformation, and visualization. Key libraries discussed are Deedle for exploratory data analysis and the F# R Provider for integration with R packages. Examples are provided demonstrating use of these libraries for understanding time series data and US debt. Support for the FsLab project is encouraged through contributions, feedback, and integration with other packages.
Creating Domain Specific Languages in F#
When designing software, we often need to solve numerous instances of the same problem. When designing user-interfaces, we need to describe the layout and interaction. When financial systems, we need to describe a wide range of financial contracts or, for example, recognize different patterns in price change.
Domain Specific Languages (DSLs) give us a way to solve such repeating problems. By designing a composable functional library, we can build an expressive language for describing our problems. Using the flexible F# syntax, we can get code that even non-programmers can understand.
In this practically oriented talk, we'll develop a number of sample DSLs, ending with realistic examples. We'll cover both basic principles of DSL design as well as advanced tricks, such as using the F# 3.0 query syntax.
How F# Learned to Stop Worrying and Love the Data
The world of data speaks a different language than the world of programming languages. It uses REST, SQL database schema, XML, JSON while programming languages only understand types and classes. This causes big confusion when we try to access data from programming languages, especially from those with (otherwise very useful) static type systems.
How can a programming language learn to understand data? In this talk, I'll show how this is done using type providers in F# 3.0. You'll see how integrating data into the programming language opens the possibilities for creating exciting applications.
Information-rich programming in F# (ML Workshop 2012)
We live in an information-rich world that provides huge opportunities for programmers to explore and create exciting applications. Traditionally, statically typed programming languages have not been aware of the data types that are implicitly available in the outer world such as the web, databases and semi-structured files. This tutorial presents the recent work on F# Type Providers - a language mechanism that enables a smooth integration of diverse data sources into an ML-style programming language. As a case study, we look at a type provider for accessing the world development indicators from the World Bank and we will discuss some intriguing research problems associated with mapping real-world data into an ML-style type system.
F# Type Providers in Depth
Talk slides from the Functional Programming eXchange 2012 on F# type providers. Examples include WorldBank data, SQL, OData and WSDL as well as structure inference for XML files.
Asynchronous programming in F# (QCon 2012)
Asynchronous programming on the server (using F# agents) and on the client (using Pit framework to translate F# to JavaScript).
Queries in general purpose languages
This document discusses representing queries in general purpose programming languages. It covers relational algebra and monads as theoretical foundations. It also discusses specific query implementations in Haskell, C#, and F#. Haskell uses monad comprehensions while C# uses LINQ and F# allows custom query operators. Key topics are expressing queries, compiling queries to SQL efficiently, and dealing with functions in SQL code.
Docase notation for Haskell
Slides from a brief presentation about the 'docase' notation that I did at Haskell Hackathon in Cambridge. The notation makes it easier to work with monads that have some additional operations (such as Par monad or Parsers).
Accessing loosely structured data from F# and C#
Slides from my talk at GOTO 2011. The presentation discusses how to bridge the impedance mismatch between the structure used in programming languages (classes, records, unions, ...) and structure used in data sources (database schema, XML file or JSON document). The talk shows how to solve this problem at three scales - using dynamic typing, by defining structure explicitly and using F# type providers.
F# on the Server-Side
Talk about server-side programming in F# from Functional Programming eXchange 2011 at SkillsMatter. The talk progresses from callback-based programming to asynchronous workflows and to agents in F#.
Teaching F#
One of the key concepts of functional programming is compositionality – the fact that we can build complex software using several basic “building blocks” and just a few ways of combining them. In this talk, I’ll demonstrate how we can teach this concept using F#. We’ll start with a basic example of this approach that even high-school students can easily understand – numerical expressions. Then we’ll move to more exciting examples of using library for composing 3D graphics. We’ll see that creating a fractal tree is not much more complicated than calculating the area of a triangle.
The recording is available online at: http://www.communityforfsharp.net/
Concurrent programming with Agents
This document discusses building concurrent programs using agents. It introduces agents and describes how they exchange messages and react in a reactive way. Inside an agent's brain, the document explains how agents can have a single state or multiple states implemented as a state machine. Agents communicate through messages and events to decouple them. Reusable agents like a bulking agent and blocking queue agent are presented. The document concludes with discussing how to organize large networks of agents using patterns like worker agents, layered networks, and pipeline processing.
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Academia
- 1. Cambridge, MA November 5, 2010 F# in Education Workshop F# in Academia Going cross-platform with F# for MonoDevelop Tomas Petricek tomas@tomasp.net http://tomasp.net/blog
- 2. F# doesn’t work on Mac & Linux
- 3. F# doesn’t work well on Mac & Linux
- 4. F# developer tools don’t work on Mac & Linux
- 5. F# has great developer tools on Mac & Linux Introducing F# add-in for MonoDevelop
- 6. F# in Academia • Good cross-platform developer tools for F# – Using cross-platform MonoDevelop IDE for Mono – F# add-in provides IntelliSense and F# interactive – Not aimed at large-scale business applications • Demonstration – how can universities use F#? – Teaching (functional) programming – For statistics and data analysis – Functional programming research
- 8. F# for Teaching • F# is a great language for teaching – Practical functional programming – Programming language concepts and principles – Introducing computer programming • Introduction to (functional) programming – Solid and useful mathematical foundations – Gives students practical experience – Intriguing examples are a great motivation
- 9. Composing 3D objects in a functional way Demonstration
- 11. F# for Data Processing • What makes F# great for working with data? – Productive and efficient language – F# Interactive environment – Useful features such as units of measure • Many scientists use F# already – Genome sequencing, Machine learning – Can be used on multiple platforms now…
- 12. Downloading and analyzing stock data Demonstration
- 14. F# for Language Research • Building the open-source version of F# – Release contains command line tools – Integrates into MonoDevelop with no effort – Auto-completion & tool-tips “just work” • Examples of existing F# extensions – Joinads: Language extension for reactive, concurrent and parallel programming – F7: Refinement Types for F#
- 15. Adding “joinads” to F# in MonoDevelop Demonstration
- 16. Functional Variations & Teaching • Web sites for F# in Academia – Teaching, Working, Research – Home for the MonoDevelop plug-in – Personal community project • If you’re interested, please get in touch! • Two addresses to remember www.functional-teaching.net www.functional-variations.net
- 17. Summary • F# is a great language for Academia – Consistent cross-platform feel with MonoDevelop – Lightweight, but with all modern features • Uses of F# in Academia – Teaching (functional) programming – Data analysis and statistics – Programming language research
- 18. Links Contact: Tomas Petricek Mail: tomas@tomasp.net Web: http://tomasp.net/blog Get involved! http://functional-variations.net http://functional-teaching.net